||Data-driven machine algorithms may be used in hydrology and water resources management. These methods, which originated from artificial intelligence, have been successfully used in water resources planning, management, and control. Researchers and practitioners in hydroclimatology sciences may also be interested in applying these new methods to their work. The chapter first illustrates the machine-learning algorithms as a downscaling approach by describing principles and brief details. Then, it describes an example of the authors; work on projecting precipitation using decision tree algorithms. The chapter also covers another application that includes use of artificial neural network (ANN) in rainfall-runoff modeling. Finally, the chapter draws relevant conclusions on the applicability of the mentioned methods and the future role of computational intelligence in modeling and planning of water resources.